Mapping continued brain growth and gray matter density reduction in dorsal frontal cortex: Inverse relationships during postadolescent brain maturation

Abstract

Recent in vivo structural imaging studies have shown spatial and temporal patterns of brain maturation between childhood, adolescence, and young adulthood that are generally consistent with postmortem studies of cellular maturational events such as increased myelination and synaptic pruning. In this study, we conducted detailed spatial and temporal analyses of growth and gray matter density at the cortical surface of the brain in a group of 35 normally developing children, adolescents, and young adults. To accomplish this, we used high-resolution magnetic resonance imaging and novel computational image analysis techniques. For the first time, in this report we have mapped the continued postadolescent brain growth that occurs primarily in the dorsal aspects of the frontal lobe bilaterally and in the posterior temporo-occipital junction bilaterally. Notably, maps of the spatial distribution of postadolescent cortical gray matter density reduction are highly consistent with maps of the spatial distribution of postadolescent brain growth, showing an inverse relationship between cortical gray matter density reduction and brain growth primarily in the superior frontal regions that control executive cognitive functioning. Inverse relationships are not as robust in the posterior temporo-occipital junction where gray matter density reduction is much less prominent despite late brain growth in these regions between adolescence and adulthood. Overall brain growth is not significant between childhood and adolescence, but close spatial relationships between gray matter density reduction and brain growth are observed in the dorsal parietal and frontal cortex. These results suggest that progressive cellular maturational events, such as increased myelination, may play as prominent a role during the postadolescent years as regressive events, such as synaptic pruning, in determining the ultimate density of mature frontal lobe cortical gray matter.

Fig. 1.

Gray matter density age effect statistical maps (left, right, andtop views) showing gray matter density changes between childhood and adolescence (A) and between adolescence and adulthood (B). Anatomically, the central sulcus and sylvian fissure are shown inblack. Shades of green toyellow represent negative Pearson's correlation coefficients (gray matter loss with increasing age), and shades ofblue, purple, and pinkrepresent positive Pearson's correlation coefficients (gray matter gain with age) according to the color baron the right (range of Pearson's correlation coefficients from −1.0 to 1.0). Regions shown in redcorrespond to correlation coefficients that have significant negative age effects at a threshold of p = 0.05 (gray matter loss), and regions shown in white correspond to significant positive age effects at a threshold ofp = 0.05 (gray matter density gain).C, Statistical map of the Fisher'sZ transformation of the difference between Pearson's correlation coefficients for the child to adolescent and the adolescent to adult contrasts (see color bar onright representing Z scores from −5.0 to 5.0). Shades of green to yellow represent regions where the age effects are more significant in the adolescent to adult contrast (B) than in the child to adolescent contrast (A). Highlighted inred are the regions where the difference between Pearson's correlation coefficients is statistically significant (p = 0.05). Shades of blue,purple, and pink represent regions where the age effects are more significant in the child to adolescent contrast than the adolescent to adult contrast. Highlighted inwhite are regions where these effects are significant at a threshold of p = 0.05.

Fig. 2.

DFC age–effect statistical maps (left, right, and topviews) showing changes in DFC between childhood and adolescence (A) and between adolescence and adulthood (B). Anatomically, the central sulcus and sylvian fissure are shown in black. Shades ofgreen to yellow represent positive Pearson's correlation coefficients (increased DFC or brain growth), and shades of blue, purple, andpink represent negative Pearson's correlation coefficients (decreased DFC or shrinkage) according to the color bar on the right (range of Pearson's correlation coefficients from −1.0 to 1.0). Regions shown inred correspond to correlation coefficients that have significant positive age effects at a threshold ofp = 0.05 (brain growth), and regions shown inwhite correspond to significant negative age effects at a threshold of p = 0.05 (brain shrinkage).C, Statistical map of the Fisher's Ztransformation of the difference between Pearson's correlation coefficients for the child to adolescent and the adolescent to adult contrasts (see color bar on rightrepresenting Z scores from −5.0 to 5.0). Shades ofgreen to yellow represent regions where the age effects are more significant in the adolescent to adult contrast (B) than in the child to adolescent contrast (A). Highlighted in redare the regions where the difference between Pearson's correlation coefficients is statistically significant (p= 0.05). Shades of blue, purple, andpink represent regions where the age effects are more significant in the child to adolescent contrast than the adolescent to adult contrast. Highlighted in white are regions where these effects are significant at a threshold ofp = 0.05. Note the sign of the differences between contrasts is opposite to that in the difference map for the gray matter density contrasts because of the inverse relationship between gray matter density (negative effects) and late brain growth (positive effects).

Fig. 3.

A, Composite statistical map (top view) showing the correspondence in age effects for changes in DFC and changes in gray matter in the child to adolescent contrast. Shown in green is the Pearson's correlation map of all positive correlation coefficients for DFC (also seen in Fig.2), and in blue is the probability map of all regions of significant gray matter loss (surface point significance threshold,p = 0.05, as shown in Fig. 1). Inred are regions of overlap in the gray and DFC statistical maps. B, Similar composite map for the adolescent to adult age effects. Note the highly spatially consistent relationship between brain growth and reduction in gray matter density. The shapes of the regions of greatest age-related change for the two maps (gray matter and DFC) are nearly identical in many frontal regions in the adolescent to adult contrast. Very few regions of gray matter density reduction fall outside regions of increases in DFC. C, D (left, right, andtop views), Difference between Pearson's correlation coefficients for the age effects for gray matter density and the age effects for DFC between childhood and adolescence (C) and between adolescence and adulthood (D). These maps are similar to those of the difference between correlation coefficients for age effects of gray matter and DFC shown in Figures 1 and 2 but instead highlight the correlation between regions of greatest change in the two separate features of brain maturation measured here (DFC and gray matter density). The color bar represents correspondingZ scores ranging from −5.0 to 5.0 for the difference between correlation coefficients for DFC and gray matter. Highlighted in red are regions of significant negative correlations between DFC and gray matter density (p = 0.05), showing that the relationship between regions of greatest gray matter density reduction are statistically the same as the regions with the greatest brain growth, particularly in the adolescent to adulthood years. Highlighted in white are the regions where the difference between correlation coefficients for the gray matter and DFC maps is positive, indicating that the change with age is in the same direction for both variables (i.e., increased DFC change goes with increased gray matter density change).

Fig. 4.

Statistical map of the correlation between gray matter density and DFC across all subjects studied. Anatomically, the central sulcus and sylvian fissure are highlighted. Shown in shades of blue, purple, andpink are regions where the correlation is positive (i.e., greater gray density associated with greater DFC), and in shades of green to yellow are regions where the correlation between DFC and gray matter density is negative. Highlighted in red are regions where the negative relationship is highly statistically significant (p = 0.000001). Note that none of the positive correlations between DFC and gray matter density was significant, even when p = 0.01 was used as a threshold.

Fig. 5.

Differences between groups in DFC shown in millimeters in color (according to the color bar) between childhood and adolescence in both nonscaled (A) and scaled (C) image data sets. Differences between adolescents and adults are also shown in nonscaled (B) and scaled (D) images. Anatomically, the central sulcus and sylvian fissure are shown in black. The maps in the scaled image space allow an assessment of the magnitude (in millimeters) of differences in DFC shown as statistical maps in Figure 2. The samecolor bar applies to both nonscaled and scaled images; regions of brain growth between the younger and older age group tested are shown in dark blue, purple, andpink, and regions of shrinkage between the younger and older groups tested are shown in red,yellow, green, and light blue. Note that whether or not brain size correction is made with scaling, dorsal frontal and posterior temporal lobes show evidence for continued growth after adolescence. Other less robust regions of brain growth or shrinkage are “scaled” out when brain size correction is used to control individual differences.